A Robust Seamless Localization Framework Based on Wi-Fi FTM / GNSS and Built-In Sensors

Abstract

Global Navigation Satellite System (GNSS) has been widely applied for outdoor localization while it is still challenging to realize seamless positioning due to the limited coverage of accurate indoor location sources. This letter proposes a robust seamless localization framework using the combination of GNSS, Wi-Fi Fine Time Measurement and built-in sensors (SL-GWBS). Pedestrian dead reckoning and magnetic detection are used to decrease the cumulative error of inertial navigation system for accurate heading and speed estimation, and an adaptive multi-model based extended Kalman filter is adopted to realize concrete localization towards different integration methods of location sources. The experimental results demonstrate the meter-level accuracy of the proposed SL-GWBS.